On-line Recognition of Critical Driving Situations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F21%3A00351008" target="_blank" >RIV/68407700:21260/21:00351008 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.14311/NNW.2021.31.012" target="_blank" >https://doi.org/10.14311/NNW.2021.31.012</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2021.31.012" target="_blank" >10.14311/NNW.2021.31.012</a>
Alternative languages
Result language
angličtina
Original language name
On-line Recognition of Critical Driving Situations
Original language description
According to the statistics about vehicle accidents, there are many causes such as traffic violations, reduced concentration, micro sleep, hasty aggression, but the most frequent cause of accidents at highways is a carelessness of the driver and violation of keeping a safe distance. Producers of vehicles try to take into account this situation by development of assistance systems which are able to avoid accidents or at least to mitigate its consequences. This urgent situation leaded to the described project of investigation of behavior of drivers in dangerous situations occurring in vehicle driving. The research is to help in solution of the present unsatisfactory situation in driving accidents. The developed decisionmaking algorithm of detection serious driving situations that can lead to accidents was tested in the laboratory of driving simulators in FTS CTU, Prague. The data for its testing resembled highway traffic.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
2336-4335
Volume of the periodical
31
Issue of the periodical within the volume
3
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
12
Pages from-to
227-238
UT code for WoS article
000691212500004
EID of the result in the Scopus database
2-s2.0-85115446725